AI, Never forget
We track, test and explain how artificial intelligence remembers, forgets and relearns — across models, updates and time.
Every AI system remembers something. Almost none remember well.
Ask an AI to recall something you mentioned an hour ago, and the answer depends on more than the model itself — on how long the conversation has run, how the system was built to hold context, and what it was designed to let go of.
Some information survives. Most quietly doesn't. Context gets compressed, recall gets approximate, and what feels like memory is often something closer to a good guess.
AINeverForget exists to track exactly where that line falls — model by model, update by update.
Original experiments on memory, context, recall and degradation.
Run on real models, published with full method — including where the method falls short.
5 AIs. One Memory.
The same set of facts. The same conversation length. Five different models. How much actually survives — and how does it fail?
A living, comparative record — across dimensions, not one score.
Memory isn't one number. It's tracked here across the ways it actually breaks down.
Explanations, history and analysis — the reading behind the research.
What "context window" actually means
The jargon behind why AI forgets mid-conversation, explained without the hand-waving.
MemoryA short history of AI memory
From stateless chatbots to systems that carry something forward — how we got here.
KnowledgeBuilding a knowledge system an AI can actually use
Personal knowledge management is quietly becoming an AI memory problem.
Memory is becoming part of intelligence. Someone should keep track.
AINeverForget observes, tests and records how artificial memory evolves — across models, across updates, over time.
It's built around one question the rest of the industry mostly explains and rarely tests: what does AI actually remember? The record, the research and the index are how we find out.